TY - JOUR
T1 - Biological and bio-inspired materials
T2 - Multi-scale modeling, artificial intelligence approaches, and experiments
AU - Chen, Po Yu
AU - Jasiuk, Iwona
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/5/1
Y1 - 2024/5/1
N2 - Biological materials often possess remarkable properties and functionalities owing to their complex hierarchical and composite structures. Learning from nature can lead to revolutionary breakthroughs in materials science and innovative new technologies. This Special Issue titled “Biological and Bio-inspired Materials: Multi-scale Modeling and Artificial Intelligence Approaches” is a collection of research articles and comprehensive reviews utilizing multi-scale modeling, artificial intelligence approaches, and experiments to elucidate the characteristics of biological materials and design and optimize bio-inspired materials. The computational approaches of interest include but are not limited to molecular dynamics, lattice spring models, finite element analysis, genetic algorithms, neural networks, generative adversarial networks, and other modeling and artificial intelligence approaches for better understanding the structure-property relationships and underlying mechanisms of biological (natural) materials, and reproducing, designing, and optimizing bio-inspired materials. Novel experimental results, fabrication strategies, and applications of biological, bio-inspired and biomedical materials are also collected in this special issue.
AB - Biological materials often possess remarkable properties and functionalities owing to their complex hierarchical and composite structures. Learning from nature can lead to revolutionary breakthroughs in materials science and innovative new technologies. This Special Issue titled “Biological and Bio-inspired Materials: Multi-scale Modeling and Artificial Intelligence Approaches” is a collection of research articles and comprehensive reviews utilizing multi-scale modeling, artificial intelligence approaches, and experiments to elucidate the characteristics of biological materials and design and optimize bio-inspired materials. The computational approaches of interest include but are not limited to molecular dynamics, lattice spring models, finite element analysis, genetic algorithms, neural networks, generative adversarial networks, and other modeling and artificial intelligence approaches for better understanding the structure-property relationships and underlying mechanisms of biological (natural) materials, and reproducing, designing, and optimizing bio-inspired materials. Novel experimental results, fabrication strategies, and applications of biological, bio-inspired and biomedical materials are also collected in this special issue.
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U2 - 10.1016/j.jmrt.2024.05.117
DO - 10.1016/j.jmrt.2024.05.117
M3 - Article
AN - SCOPUS:85193531359
SN - 2238-7854
VL - 30
SP - 7510
EP - 7511
JO - Journal of Materials Research and Technology
JF - Journal of Materials Research and Technology
ER -